Miscellanea. Random coefficient autoregressive models for longitudinal data

Abstract

Stable autoregressive models with exogenous covariates can be used to mimic nonstationary, stabilising growth profiles in longitudinal data. If different individuals have very different trajectories, the autoregressive parameters can be interpreted as random variables varying from one individual to the next. If all random effects are assumed Gaussian, the model with be quite easy to estimate although the marginal distributions of the observations will no longer be Gaussian. However, this kind of model can only be used when the observations are equally spaced.